Audio Signature Matching for Automated Advertisement Detection
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Solution Overview
Problem
Current systems require excessive human involvement to identify advertisements in audiovisual multimedia content, as markers are often absent and advertisement locations are variable, leading to inefficiencies in removal or replacement processes.
Innovation Solution
A system and method that utilize audio signatures to determine the presence of advertisements by comparing obtained audio signatures with a database of stored signatures, reducing human intervention and enabling automatic detection and removal or replacement of advertisements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If markers are used to denote advertisement locations, then advertisement identification becomes easier, but the system requires additional components and may not be applicable to all multimedia content
Solution Approach 1:
The patent extracts the essential identifying feature (audio signature) from the multimedia content, separating the advertisement detection function from the need for external markers. By analyzing only the audio characteristics inherent in the content, the system removes the complexity of marker insertion and detection while maintaining effective advertisement identification.
Solution Approach 2:
The multimedia content itself provides the identification information through its audio signature, eliminating the need for external marker systems. The audio fingerprint embedded in the advertisement audio serves as a self-contained identifier that enables automatic detection without additional components or manual intervention.
2Measurement precision
If manual methods are used to identify advertisement locations, then precision can be maintained, but excessive human involvement and time are required
Solution Approach 1:
The patent replaces the manual mechanical process of reviewing multimedia content with an automated audio analysis system. The audio signature matching algorithm automatically compares audio fingerprints against a database, substituting human review with computational processing that achieves comparable or superior precision while dramatically reducing time requirements.
Solution Approach 2:
The system performs preliminary extraction and storage of audio signatures from multimedia content before the actual advertisement detection is needed. By pre-processing and indexing audio fingerprints in advance, the system enables rapid automated comparison and identification during playback or archiving operations, eliminating the need for time-consuming manual review.
3Extent of automation
If audio signature matching is used to detect advertisements, then automation is achieved with minimal human involvement, but the system requires sophisticated processing and comparison capabilities
Solution Approach 1:
The patent creates simplified copies of the audio content in the form of audio signatures or fingerprints - condensed representations that capture the essential identifying characteristics. These audio copies enable automated matching and comparison operations without requiring the system to process the entire original audio stream, reducing computational complexity while maintaining detection accuracy.
Data Source
AI summary
Systems and methods for determining the location of advertisements in multimedia assets are disclosed. A method includes obtaining an audio signature corresponding to a time period of a multimedia asset, identifying a match between the obtained audio signature and one or more stored audio signatures, comparing programming data of the multimedia assets of the obtained audio signature and the matching audio signatures, and determining whether the time period of the multimedia asset contains an advertisement based on the comparison of the programming data of the multimedia assets of the obtained audio signature and the one or more matching audio signatures. Another method includes identifying matches between a plurality of obtained audio signatures and a plurality of stored audio signatures, and determining whether consecutive time periods of the multimedia asset contain an advertisement based on a number of consecutive matching audio signatures of the plurality of stored audio signatures.